The perceived sharpness of a display device is an important factor for defining picture quality. For large screen display devices, as well as upscaling source signals from lower resolutions to panel resolutions of higher quality, sharpness of the display image is especially important. Conventional methods of picture quality enhancement typically employ one of unsharp masking and luma transient improvement (LTI). The conventional techniques however, do utilize the benefits of each method or correcting the defects of each method.
Unsharp masking is a conventional the oldest method of picture enhancement originally developed for dark room processing. In the conventional methods of unsharp masking, sharpness of an image was first low-pass filtered (e.g., blurred or unsharpened) such that the image was defocused. The resulting defocused negative was used as a mask for a normally processed image. Effectively, the conventional unsharp masking methods increase gain for high frequency image components. Unsharp masking is a type of technique for linear sharpening technique. FIG. 1 depicts a graphical representation 100 of a conventional linear sharpening technique. Sharpness levels of the conventional technique could be used to define the strength of linear sharpening. Although the conventional methods for linear sharpening, such as unsharp masking, have been effective for many applications, these techniques can produce two major artifacts which effect image quality. Conventional linear sharpening techniques can amplify noise appearing in an original image and further, create visible overshoot on edges of objects.
The conventional methods and techniques for LTI attempt to adaptively modify edges of a received image signal. Similar to unsharp masking techniques, conventional methods and techniques for LTI can provide image enhancement. However, the conventional methods of LTI can produce image artifacts, such as contouring and line flattening.
Although the conventional methods may be suitable for some applications, the conventional systems and methods do not apply an acceptable level of performance for sharpness enhancement of image data for all applications. Thus, there is a need in the art for systems and methods of image enhancement to utilize the benefits of enhancement techniques while minimizing their side effects.